Employment and Unemployment Trends in the Baltic Countries and Statistical Regions of Latvia, 1998–2011
Bibliographic record
Abstract
The aim of the paper is to analyse the number and proportion of employees, unemployment rates and theirterritorial trends in Latvia, and to compare them with those in Estonia and Lithuania. The paper analyses the number ofemployees at the main job, its proportion in the private sector, and unemployment rates in the Baltic countries and statisticalregions of Latvia. In 2000–2007, employment and its proportion in the private sector was on the increase. In 2008, an upwardtrend in Estonia and Lithuania started to decrease, but in Latvia number of employees and its proportion in the private sectoralready had dropped. In 2009, the number of employees continued to decline. The unemployment rate grew from 1998 to2000 and from III quarter 2008 to I quarter 2010. From 2001 to II quarter 2008, during an economic boom, it decreased to aminimum. A faster economic growth means a higher proportion of employees in the private sector; however, during theeconomic crisis, it creates more instability in the labour market than in the public sector, especially at the beginning. As thecrisis deepens, unemployment in the private sector begins to stabilize; however, it increases in the public sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".